Check out How to specify algorithms and algorithm specific options to see how to select an algorithm and specify algo_options when using maximize or minimize.

Optimizers from scipy#

estimagic supports most scipy algorithms and scipy is automatically installed when you install estimagic.

Own optimizers#

We implement a few algorithms from scratch. They are currently considered experimental.

Optimizers from the Toolkit for Advanced Optimization (TAO)#

We wrap the pounders algorithm from the Toolkit of Advanced optimization. To use it you need to have petsc4py installed.

Optimizers from the Numerical Algorithms Group (NAG)#

We wrap two algorithms from the numerical algorithms group. To use them, you need to install each of them separately:

  • pip install DFO-LS

  • pip install Py-BOBYQA

PYGMO2 Optimizers#

Please cite [algo_18] in addition to estimagic when using pygmo. estimagic supports the following pygmo2 optimizers.

The Interior Point Optimizer (ipopt)#

estimagic’s support for the Interior Point Optimizer ([algo_34], [algo_35], [algo_36], [algo_37]) is built on cyipopt, a Python wrapper for the Ipopt optimization package.

To use ipopt, you need to have cyipopt installed (conda install cyipopt).

The Fides Optimizer#

estimagic supports the Fides Optimizer. To use Fides, you need to have the fides package installed (pip install fides>=0.7.4, make sure you have at least 0.7.1).

The NLOPT Optimizers (nlopt)#

estimagic supports the following NLOPT algorithms. Please add the appropriate citations in addition to estimagic when using an NLOPT algorithm. To install nlopt run conda install nlopt.



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